Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Active power generator 2, Total accumulated [W] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Active power limit [W] is highly overall correlated with HourCounters Average GridOn Avg. [h]High correlation
Active power limit source is highly overall correlated with Power factor set point and 1 other fieldsHigh correlation
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 3 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°] and 2 other fieldsHigh correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CosPhi Avg. is highly overall correlated with Production LatestAverage Active Power Gen 0 Avg. [W] and 1 other fieldsHigh correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower Min. [W] is highly overall correlated with Grid Production Power Min. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power Min. [W] is highly overall correlated with Grid Production PossiblePower Min. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 8 other fieldsHigh correlation
Grid Production ReactivePower Max. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 2 other fieldsHigh correlation
Grid Production ReactivePower StdDev [W] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 1 other fieldsHigh correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase3 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with HourCounters Average Gen2 Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Blades PitchAngle Min. [°] and 7 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average GridOn Avg. [h] is highly overall correlated with Active power limit [W]High correlation
HourCounters Average Run Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average ServiceOn Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h]High correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with HourCounters Average Run Avg. [h]High correlation
Power factor set point is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Power factor set point source is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production CosPhi Avg. and 3 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production CosPhi Avg. and 4 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly overall correlated with Blades PitchAngle StdDev [°] and 3 other fieldsHigh correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 3 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (60.0%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (53.1%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (56.0%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (55.9%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (78.9%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (75.6%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (76.5%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (77.5%) Imbalance
Generator SlipRing Temp. Avg. [°C] is highly imbalanced (55.9%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (75.1%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (75.3%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (58.9%) Imbalance
Gear Oil TemperatureLevel1 Avg. [°C] is highly imbalanced (55.9%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (70.8%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (68.5%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (64.5%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (52.8%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (58.7%) Imbalance
Nacelle Temp. Avg. [°C] is highly imbalanced (65.1%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (53.0%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (58.2%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (88.8%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (86.1%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (91.1%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (70.0%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (79.6%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (82.6%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (68.3%) Imbalance
Grid RotorInvPhase1 Temp. Avg. [°C] is highly imbalanced (60.0%) Imbalance
Grid RotorInvPhase2 Temp. Avg. [°C] is highly imbalanced (60.4%) Imbalance
Grid RotorInvPhase3 Temp. Avg. [°C] is highly imbalanced (56.7%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (74.9%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (66.7%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (95.6%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (91.9%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (91.4%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (91.4%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (72.7%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (72.9%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (74.0%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (71.5%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (67.1%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (66.5%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (72.3%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (54.7%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (80.2%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (76.7%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (75.5%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (77.4%) Imbalance
Active power limit [W] is highly imbalanced (99.1%) Imbalance
Active power limit source is highly imbalanced (99.9%) Imbalance
Power factor set point is highly imbalanced (99.9%) Imbalance
Power factor set point source is highly imbalanced (99.9%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (91.2%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (75.1%) Imbalance
Controller Hub Temp. Avg. [°C] is highly imbalanced (73.4%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (61.7%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (69.9%) Imbalance
Controller VCP WaterTemp. Avg. [°C] is highly imbalanced (55.0%) Imbalance
Spinner Temp. Avg. [°C] is highly imbalanced (64.5%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (54.6%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (51.6%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (55.6%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (80.5%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (79.3%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (82.0%) Imbalance
HVTrafo AirOutlet Temp. Avg. [°C] is highly imbalanced (51.8%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (99.4%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (98.1%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (97.5%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (96.0%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (78.9%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (59.3%) Imbalance
HourCounters Average Yaw Avg. [h] is highly imbalanced (56.8%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (98.6%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (96.4%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (66.0%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (95.8%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (67.0%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (81.9%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (71.4%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (75.7%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (64.7%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (59.0%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (55.5%) Imbalance
Total Active power [W] is highly imbalanced (99.8%) Imbalance
Reactive power generator 0,Total accumulated [var] is highly imbalanced (96.7%) Imbalance
Total reactive power [var] is highly imbalanced (94.9%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-14 17:17:57.561295
Analysis finished2025-05-14 17:18:26.486395
Duration28.93 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-14T19:18:26.526940image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T19:18:26.746684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24129 
1
 
2079

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24129
92.1%
1 2079
 
7.9%

Length

2025-05-14T19:18:26.820004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:26.855328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24129
92.1%
1 2079
 
7.9%

Most occurring characters

ValueCountFrequency (%)
0 24129
92.1%
1 2079
 
7.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24129
92.1%
1 2079
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24129
92.1%
1 2079
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24129
92.1%
1 2079
 
7.9%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23589 
1
2619 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23589
90.0%
1 2619
 
10.0%

Length

2025-05-14T19:18:26.898036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:26.934467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23589
90.0%
1 2619
 
10.0%

Most occurring characters

ValueCountFrequency (%)
0 23589
90.0%
1 2619
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23589
90.0%
1 2619
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23589
90.0%
1 2619
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23589
90.0%
1 2619
 
10.0%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23823 
1
2385 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23823
90.9%
1 2385
 
9.1%

Length

2025-05-14T19:18:26.979297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.016996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23823
90.9%
1 2385
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23823
90.9%
1 2385
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23823
90.9%
1 2385
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23823
90.9%
1 2385
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23823
90.9%
1 2385
 
9.1%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23810 
1
2398 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23810
90.9%
1 2398
 
9.1%

Length

2025-05-14T19:18:27.061100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.097110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23810
90.9%
1 2398
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23810
90.9%
1 2398
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23810
90.9%
1 2398
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23810
90.9%
1 2398
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23810
90.9%
1 2398
 
9.1%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25335 
1
 
873

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Length

2025-05-14T19:18:27.142176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.177527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25335
96.7%
1 873
 
3.3%

Generator Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25151 
1
 
1057

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25151
96.0%
1 1057
 
4.0%

Length

2025-05-14T19:18:27.220641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.255985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25151
96.0%
1 1057
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25151
96.0%
1 1057
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25151
96.0%
1 1057
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25151
96.0%
1 1057
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25151
96.0%
1 1057
 
4.0%

Generator Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25201 
1
 
1007

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25201
96.2%
1 1007
 
3.8%

Length

2025-05-14T19:18:27.298372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.335679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25201
96.2%
1 1007
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25201
96.2%
1 1007
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25201
96.2%
1 1007
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25201
96.2%
1 1007
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25201
96.2%
1 1007
 
3.8%

Generator Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25255 
1
 
953

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25255
96.4%
1 953
 
3.6%

Length

2025-05-14T19:18:27.378001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.413690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25255
96.4%
1 953
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25255
96.4%
1 953
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25255
96.4%
1 953
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25255
96.4%
1 953
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25255
96.4%
1 953
 
3.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23811 
1
2397 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23811
90.9%
1 2397
 
9.1%

Length

2025-05-14T19:18:27.457091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.493314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23811
90.9%
1 2397
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23811
90.9%
1 2397
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23811
90.9%
1 2397
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23811
90.9%
1 2397
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23811
90.9%
1 2397
 
9.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25119 
1
 
1089

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25119
95.8%
1 1089
 
4.2%

Length

2025-05-14T19:18:27.537188image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.574547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25119
95.8%
1 1089
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25119
95.8%
1 1089
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25119
95.8%
1 1089
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25119
95.8%
1 1089
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25119
95.8%
1 1089
 
4.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22718 
1
3490 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22718
86.7%
1 3490
 
13.3%

Length

2025-05-14T19:18:27.616735image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.652894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22718
86.7%
1 3490
 
13.3%

Most occurring characters

ValueCountFrequency (%)
0 22718
86.7%
1 3490
 
13.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22718
86.7%
1 3490
 
13.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22718
86.7%
1 3490
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22718
86.7%
1 3490
 
13.3%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25132 
1
 
1076

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25132
95.9%
1 1076
 
4.1%

Length

2025-05-14T19:18:27.698637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.734199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25132
95.9%
1 1076
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25132
95.9%
1 1076
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25132
95.9%
1 1076
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25132
95.9%
1 1076
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25132
95.9%
1 1076
 
4.1%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:27.776220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.811172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:27.850108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.883144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24044 
1
 
2164

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24044
91.7%
1 2164
 
8.3%

Length

2025-05-14T19:18:27.924087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:27.960814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24044
91.7%
1 2164
 
8.3%

Most occurring characters

ValueCountFrequency (%)
0 24044
91.7%
1 2164
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24044
91.7%
1 2164
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24044
91.7%
1 2164
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24044
91.7%
1 2164
 
8.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23814 
1
2394 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23814
90.9%
1 2394
 
9.1%

Length

2025-05-14T19:18:28.004793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.042738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23814
90.9%
1 2394
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23814
90.9%
1 2394
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23814
90.9%
1 2394
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23814
90.9%
1 2394
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23814
90.9%
1 2394
 
9.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:28.086985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.120091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24863 
1
 
1345

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Length

2025-05-14T19:18:28.160892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.196269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Most occurring characters

ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24719 
1
 
1489

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Length

2025-05-14T19:18:28.238356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.275535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24719
94.3%
1 1489
 
5.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24451 
1
 
1757

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Length

2025-05-14T19:18:28.317990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.353788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Most occurring characters

ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23559 
1
2649 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23559
89.9%
1 2649
 
10.1%

Length

2025-05-14T19:18:28.397415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.433527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23559
89.9%
1 2649
 
10.1%

Most occurring characters

ValueCountFrequency (%)
0 23559
89.9%
1 2649
 
10.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23559
89.9%
1 2649
 
10.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23559
89.9%
1 2649
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23559
89.9%
1 2649
 
10.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24028 
1
 
2180

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24028
91.7%
1 2180
 
8.3%

Length

2025-05-14T19:18:28.477396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.515028image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24028
91.7%
1 2180
 
8.3%

Most occurring characters

ValueCountFrequency (%)
0 24028
91.7%
1 2180
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24028
91.7%
1 2180
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24028
91.7%
1 2180
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24028
91.7%
1 2180
 
8.3%

Nacelle Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24492 
1
 
1716

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Length

2025-05-14T19:18:28.558991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.595252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Most occurring characters

ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23575 
1
2633 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23575
90.0%
1 2633
 
10.0%

Length

2025-05-14T19:18:28.639044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.675314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23575
90.0%
1 2633
 
10.0%

Most occurring characters

ValueCountFrequency (%)
0 23575
90.0%
1 2633
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23575
90.0%
1 2633
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23575
90.0%
1 2633
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23575
90.0%
1 2633
 
10.0%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23044 
1
3164 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23044
87.9%
1 3164
 
12.1%

Length

2025-05-14T19:18:28.719784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.758024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23044
87.9%
1 3164
 
12.1%

Most occurring characters

ValueCountFrequency (%)
0 23044
87.9%
1 3164
 
12.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23044
87.9%
1 3164
 
12.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23044
87.9%
1 3164
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23044
87.9%
1 3164
 
12.1%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23990 
1
 
2218

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23990
91.5%
1 2218
 
8.5%

Length

2025-05-14T19:18:28.802184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.838402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23990
91.5%
1 2218
 
8.5%

Most occurring characters

ValueCountFrequency (%)
0 23990
91.5%
1 2218
 
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23990
91.5%
1 2218
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23990
91.5%
1 2218
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23990
91.5%
1 2218
 
8.5%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23124 
1
3084 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23124
88.2%
1 3084
 
11.8%

Length

2025-05-14T19:18:28.884293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:28.920792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23124
88.2%
1 3084
 
11.8%

Most occurring characters

ValueCountFrequency (%)
0 23124
88.2%
1 3084
 
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23124
88.2%
1 3084
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23124
88.2%
1 3084
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23124
88.2%
1 3084
 
11.8%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25818 
1
 
390

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25818
98.5%
1 390
 
1.5%

Length

2025-05-14T19:18:28.965204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.002934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25818
98.5%
1 390
 
1.5%

Most occurring characters

ValueCountFrequency (%)
0 25818
98.5%
1 390
 
1.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25818
98.5%
1 390
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25818
98.5%
1 390
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25818
98.5%
1 390
 
1.5%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25694 
1
 
514

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25694
98.0%
1 514
 
2.0%

Length

2025-05-14T19:18:29.045026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.080799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25694
98.0%
1 514
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 25694
98.0%
1 514
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25694
98.0%
1 514
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25694
98.0%
1 514
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25694
98.0%
1 514
 
2.0%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25915 
1
 
293

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25915
98.9%
1 293
 
1.1%

Length

2025-05-14T19:18:29.124864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.160698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25915
98.9%
1 293
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25915
98.9%
1 293
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25915
98.9%
1 293
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25915
98.9%
1 293
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25915
98.9%
1 293
 
1.1%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24810 
1
 
1398

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24810
94.7%
1 1398
 
5.3%

Length

2025-05-14T19:18:29.202746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.240741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24810
94.7%
1 1398
 
5.3%

Most occurring characters

ValueCountFrequency (%)
0 24810
94.7%
1 1398
 
5.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24810
94.7%
1 1398
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24810
94.7%
1 1398
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24810
94.7%
1 1398
 
5.3%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25373 
1
 
835

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25373
96.8%
1 835
 
3.2%

Length

2025-05-14T19:18:29.283072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.318617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25373
96.8%
1 835
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25373
96.8%
1 835
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25373
96.8%
1 835
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25373
96.8%
1 835
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25373
96.8%
1 835
 
3.2%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25525 
1
 
683

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25525
97.4%
1 683
 
2.6%

Length

2025-05-14T19:18:29.362775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.398167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25525
97.4%
1 683
 
2.6%

Most occurring characters

ValueCountFrequency (%)
0 25525
97.4%
1 683
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25525
97.4%
1 683
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25525
97.4%
1 683
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25525
97.4%
1 683
 
2.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22853 
1
3355 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22853
87.2%
1 3355
 
12.8%

Length

2025-05-14T19:18:29.440169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.478034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22853
87.2%
1 3355
 
12.8%

Most occurring characters

ValueCountFrequency (%)
0 22853
87.2%
1 3355
 
12.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22853
87.2%
1 3355
 
12.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22853
87.2%
1 3355
 
12.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22853
87.2%
1 3355
 
12.8%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:29.521981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.555178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24704 
1
 
1504

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24704
94.3%
1 1504
 
5.7%

Length

2025-05-14T19:18:29.736662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.772203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24704
94.3%
1 1504
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24704
94.3%
1 1504
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24704
94.3%
1 1504
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24704
94.3%
1 1504
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24704
94.3%
1 1504
 
5.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24125 
1
 
2083

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24125
92.1%
1 2083
 
7.9%

Length

2025-05-14T19:18:29.814187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.851136image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24125
92.1%
1 2083
 
7.9%

Most occurring characters

ValueCountFrequency (%)
0 24125
92.1%
1 2083
 
7.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24125
92.1%
1 2083
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24125
92.1%
1 2083
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24125
92.1%
1 2083
 
7.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24154 
1
 
2054

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24154
92.2%
1 2054
 
7.8%

Length

2025-05-14T19:18:29.893133image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:29.928680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24154
92.2%
1 2054
 
7.8%

Most occurring characters

ValueCountFrequency (%)
0 24154
92.2%
1 2054
 
7.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24154
92.2%
1 2054
 
7.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24154
92.2%
1 2054
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24154
92.2%
1 2054
 
7.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23876 
1
 
2332

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Length

2025-05-14T19:18:29.972938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.009539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25108 
1
 
1100

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25108
95.8%
1 1100
 
4.2%

Length

2025-05-14T19:18:30.053473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.090557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25108
95.8%
1 1100
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25108
95.8%
1 1100
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25108
95.8%
1 1100
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25108
95.8%
1 1100
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25108
95.8%
1 1100
 
4.2%

Grid Production CosPhi Avg.
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24596 
1
 
1612

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Length

2025-05-14T19:18:30.132855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.168072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring characters

ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26082 
1
 
126

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26082
99.5%
1 126
 
0.5%

Length

2025-05-14T19:18:30.211867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.247450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26082
99.5%
1 126
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26082
99.5%
1 126
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26082
99.5%
1 126
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26082
99.5%
1 126
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26082
99.5%
1 126
 
0.5%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25945 
1
 
263

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25945
99.0%
1 263
 
1.0%

Length

2025-05-14T19:18:30.291237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.327205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25945
99.0%
1 263
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25945
99.0%
1 263
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25945
99.0%
1 263
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25945
99.0%
1 263
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25945
99.0%
1 263
 
1.0%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25927 
1
 
281

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25927
98.9%
1 281
 
1.1%

Length

2025-05-14T19:18:30.369557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.406511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25927
98.9%
1 281
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25927
98.9%
1 281
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25927
98.9%
1 281
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25927
98.9%
1 281
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25927
98.9%
1 281
 
1.1%

Grid Production VoltagePhase3 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25926 
1
 
282

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25926
98.9%
1 282
 
1.1%

Length

2025-05-14T19:18:30.448520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.483823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25926
98.9%
1 282
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25926
98.9%
1 282
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25926
98.9%
1 282
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25926
98.9%
1 282
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25926
98.9%
1 282
 
1.1%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24979 
1
 
1229

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Length

2025-05-14T19:18:30.527610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.563347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24992 
1
 
1216

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24992
95.4%
1 1216
 
4.6%

Length

2025-05-14T19:18:30.606242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.643492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24992
95.4%
1 1216
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 24992
95.4%
1 1216
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24992
95.4%
1 1216
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24992
95.4%
1 1216
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24992
95.4%
1 1216
 
4.6%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25055 
1
 
1153

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25055
95.6%
1 1153
 
4.4%

Length

2025-05-14T19:18:30.685802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.721333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25055
95.6%
1 1153
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25055
95.6%
1 1153
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25055
95.6%
1 1153
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25055
95.6%
1 1153
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25055
95.6%
1 1153
 
4.4%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24904 
1
 
1304

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24904
95.0%
1 1304
 
5.0%

Length

2025-05-14T19:18:30.765182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.800900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24904
95.0%
1 1304
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 24904
95.0%
1 1304
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24904
95.0%
1 1304
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24904
95.0%
1 1304
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24904
95.0%
1 1304
 
5.0%

Grid Production Power Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24625 
1
 
1583

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24625
94.0%
1 1583
 
6.0%

Length

2025-05-14T19:18:30.842807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.880022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24625
94.0%
1 1583
 
6.0%

Most occurring characters

ValueCountFrequency (%)
0 24625
94.0%
1 1583
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24625
94.0%
1 1583
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24625
94.0%
1 1583
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24625
94.0%
1 1583
 
6.0%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24586 
1
 
1622

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24586
93.8%
1 1622
 
6.2%

Length

2025-05-14T19:18:30.922080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:30.957467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24586
93.8%
1 1622
 
6.2%

Most occurring characters

ValueCountFrequency (%)
0 24586
93.8%
1 1622
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24586
93.8%
1 1622
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24586
93.8%
1 1622
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24586
93.8%
1 1622
 
6.2%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24955 
1
 
1253

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24955
95.2%
1 1253
 
4.8%

Length

2025-05-14T19:18:31.001857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.037476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24955
95.2%
1 1253
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0 24955
95.2%
1 1253
 
4.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24955
95.2%
1 1253
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24955
95.2%
1 1253
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24955
95.2%
1 1253
 
4.8%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23720 
1
2488 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23720
90.5%
1 2488
 
9.5%

Length

2025-05-14T19:18:31.079395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.117039image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23720
90.5%
1 2488
 
9.5%

Most occurring characters

ValueCountFrequency (%)
0 23720
90.5%
1 2488
 
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23720
90.5%
1 2488
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23720
90.5%
1 2488
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23720
90.5%
1 2488
 
9.5%

Grid Production ReactivePower Max. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22839 
1
3369 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22839
87.1%
1 3369
 
12.9%

Length

2025-05-14T19:18:31.160889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.196967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22839
87.1%
1 3369
 
12.9%

Most occurring characters

ValueCountFrequency (%)
0 22839
87.1%
1 3369
 
12.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22839
87.1%
1 3369
 
12.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22839
87.1%
1 3369
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22839
87.1%
1 3369
 
12.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22628 
1
3580 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Length

2025-05-14T19:18:31.243010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.279046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Most occurring characters

ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Grid Production ReactivePower StdDev [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21909 
1
4299 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21909
83.6%
1 4299
 
16.4%

Length

2025-05-14T19:18:31.323435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.361516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21909
83.6%
1 4299
 
16.4%

Most occurring characters

ValueCountFrequency (%)
0 21909
83.6%
1 4299
 
16.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21909
83.6%
1 4299
 
16.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21909
83.6%
1 4299
 
16.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21909
83.6%
1 4299
 
16.4%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25405 
1
 
803

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25405
96.9%
1 803
 
3.1%

Length

2025-05-14T19:18:31.405725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.440978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25405
96.9%
1 803
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25405
96.9%
1 803
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25405
96.9%
1 803
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25405
96.9%
1 803
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25405
96.9%
1 803
 
3.1%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25214 
1
 
994

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25214
96.2%
1 994
 
3.8%

Length

2025-05-14T19:18:31.484612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.519964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25214
96.2%
1 994
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25214
96.2%
1 994
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25214
96.2%
1 994
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25214
96.2%
1 994
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25214
96.2%
1 994
 
3.8%

Grid Production PossiblePower Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25143 
1
 
1065

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25143
95.9%
1 1065
 
4.1%

Length

2025-05-14T19:18:31.562108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.599341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25143
95.9%
1 1065
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25143
95.9%
1 1065
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25143
95.9%
1 1065
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25143
95.9%
1 1065
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25143
95.9%
1 1065
 
4.1%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25253 
1
 
955

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25253
96.4%
1 955
 
3.6%

Length

2025-05-14T19:18:31.641837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.677350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25253
96.4%
1 955
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25253
96.4%
1 955
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25253
96.4%
1 955
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25253
96.4%
1 955
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25253
96.4%
1 955
 
3.6%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:31.721195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.754184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:31.793243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.828158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:31.867223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.900526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:31.941260image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:31.974645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:32.015301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.050529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:32.089988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.123833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:32.164863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.197965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:32.237202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.272276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26188 
1
 
20

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26188
99.9%
1 20
 
0.1%

Length

2025-05-14T19:18:32.313290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.350730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26188
99.9%
1 20
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26188
99.9%
1 20
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26188
99.9%
1 20
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26188
99.9%
1 20
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26188
99.9%
1 20
 
0.1%

Active power limit source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:18:32.398235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.434568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:32.480425image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.516893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:18:32.737468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.774827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Power factor set point source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:18:32.820815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.860466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25917 
1
 
291

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25917
98.9%
1 291
 
1.1%

Length

2025-05-14T19:18:32.904709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:32.943153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25917
98.9%
1 291
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25917
98.9%
1 291
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25917
98.9%
1 291
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25917
98.9%
1 291
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25917
98.9%
1 291
 
1.1%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25121 
1
 
1087

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25121
95.9%
1 1087
 
4.1%

Length

2025-05-14T19:18:32.987116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.024180image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25121
95.9%
1 1087
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25121
95.9%
1 1087
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25121
95.9%
1 1087
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25121
95.9%
1 1087
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25121
95.9%
1 1087
 
4.1%

Controller Hub Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25021 
1
 
1187

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25021
95.5%
1 1187
 
4.5%

Length

2025-05-14T19:18:33.069821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.106655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25021
95.5%
1 1187
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25021
95.5%
1 1187
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25021
95.5%
1 1187
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25021
95.5%
1 1187
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25021
95.5%
1 1187
 
4.5%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24251 
1
 
1957

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Length

2025-05-14T19:18:33.150377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.188744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Most occurring characters

ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24808 
1
 
1400

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24808
94.7%
1 1400
 
5.3%

Length

2025-05-14T19:18:33.232545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.269340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24808
94.7%
1 1400
 
5.3%

Most occurring characters

ValueCountFrequency (%)
0 24808
94.7%
1 1400
 
5.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24808
94.7%
1 1400
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24808
94.7%
1 1400
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24808
94.7%
1 1400
 
5.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23744 
1
2464 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23744
90.6%
1 2464
 
9.4%

Length

2025-05-14T19:18:33.315032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.352649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23744
90.6%
1 2464
 
9.4%

Most occurring characters

ValueCountFrequency (%)
0 23744
90.6%
1 2464
 
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23744
90.6%
1 2464
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23744
90.6%
1 2464
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23744
90.6%
1 2464
 
9.4%

Spinner Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24451 
1
 
1757

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Length

2025-05-14T19:18:33.400060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.436990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Most occurring characters

ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24451
93.3%
1 1757
 
6.7%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:33.480175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.514505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23706 
1
2502 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Length

2025-05-14T19:18:33.556716image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.594183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring characters

ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23706
90.5%
1 2502
 
9.5%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23461 
1
2747 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23461
89.5%
1 2747
 
10.5%

Length

2025-05-14T19:18:33.640047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.676361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23461
89.5%
1 2747
 
10.5%

Most occurring characters

ValueCountFrequency (%)
0 23461
89.5%
1 2747
 
10.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23461
89.5%
1 2747
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23461
89.5%
1 2747
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23461
89.5%
1 2747
 
10.5%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23793 
1
2415 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Length

2025-05-14T19:18:33.720653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.758742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Most occurring characters

ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Blades PitchAngle StdDev [°]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22897 
1
3311 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22897
87.4%
1 3311
 
12.6%

Length

2025-05-14T19:18:33.803165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.839607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22897
87.4%
1 3311
 
12.6%

Most occurring characters

ValueCountFrequency (%)
0 22897
87.4%
1 3311
 
12.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22897
87.4%
1 3311
 
12.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22897
87.4%
1 3311
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22897
87.4%
1 3311
 
12.6%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25421 
1
 
787

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Length

2025-05-14T19:18:33.885462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:33.921231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25353 
1
 
855

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25353
96.7%
1 855
 
3.3%

Length

2025-05-14T19:18:33.963060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.000576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25353
96.7%
1 855
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25353
96.7%
1 855
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25353
96.7%
1 855
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25353
96.7%
1 855
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25353
96.7%
1 855
 
3.3%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25497 
1
 
711

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Length

2025-05-14T19:18:34.043689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.079443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

HVTrafo AirOutlet Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23477 
1
2731 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23477
89.6%
1 2731
 
10.4%

Length

2025-05-14T19:18:34.123654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.159919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23477
89.6%
1 2731
 
10.4%

Most occurring characters

ValueCountFrequency (%)
0 23477
89.6%
1 2731
 
10.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23477
89.6%
1 2731
 
10.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23477
89.6%
1 2731
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23477
89.6%
1 2731
 
10.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:34.205173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.240034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

HourCounters Average GridOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26196 
1
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26196
> 99.9%
1 12
 
< 0.1%

Length

2025-05-14T19:18:34.279628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.315736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26196
> 99.9%
1 12
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26196
> 99.9%
1 12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26196
> 99.9%
1 12
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26196
> 99.9%
1 12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26196
> 99.9%
1 12
 
< 0.1%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26162 
1
 
46

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Length

2025-05-14T19:18:34.359744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.395339image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26143 
1
 
65

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26143
99.8%
1 65
 
0.2%

Length

2025-05-14T19:18:34.437349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.474700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26143
99.8%
1 65
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26143
99.8%
1 65
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26143
99.8%
1 65
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26143
99.8%
1 65
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26143
99.8%
1 65
 
0.2%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26095 
1
 
113

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26095
99.6%
1 113
 
0.4%

Length

2025-05-14T19:18:34.517086image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.552549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26095
99.6%
1 113
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26095
99.6%
1 113
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26095
99.6%
1 113
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26095
99.6%
1 113
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26095
99.6%
1 113
 
0.4%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25331 
1
 
877

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25331
96.7%
1 877
 
3.3%

Length

2025-05-14T19:18:34.596586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.632205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25331
96.7%
1 877
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25331
96.7%
1 877
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25331
96.7%
1 877
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25331
96.7%
1 877
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25331
96.7%
1 877
 
3.3%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24079 
1
 
2129

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24079
91.9%
1 2129
 
8.1%

Length

2025-05-14T19:18:34.674379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.712596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24079
91.9%
1 2129
 
8.1%

Most occurring characters

ValueCountFrequency (%)
0 24079
91.9%
1 2129
 
8.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24079
91.9%
1 2129
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24079
91.9%
1 2129
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24079
91.9%
1 2129
 
8.1%

HourCounters Average Yaw Avg. [h]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23886 
1
 
2322

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23886
91.1%
1 2322
 
8.9%

Length

2025-05-14T19:18:34.756804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.793277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23886
91.1%
1 2322
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23886
91.1%
1 2322
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23886
91.1%
1 2322
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23886
91.1%
1 2322
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23886
91.1%
1 2322
 
8.9%

HourCounters Average ServiceOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26174 
1
 
34

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Length

2025-05-14T19:18:34.839501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.875030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26108 
1
 
100

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26108
99.6%
1 100
 
0.4%

Length

2025-05-14T19:18:34.917317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:34.954828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26108
99.6%
1 100
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26108
99.6%
1 100
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26108
99.6%
1 100
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26108
99.6%
1 100
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26108
99.6%
1 100
 
0.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24555 
1
 
1653

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24555
93.7%
1 1653
 
6.3%

Length

2025-05-14T19:18:34.997567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.033932image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24555
93.7%
1 1653
 
6.3%

Most occurring characters

ValueCountFrequency (%)
0 24555
93.7%
1 1653
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24555
93.7%
1 1653
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24555
93.7%
1 1653
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24555
93.7%
1 1653
 
6.3%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26088 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26088
99.5%
1 120
 
0.5%

Length

2025-05-14T19:18:35.078419image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.114050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26088
99.5%
1 120
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26088
99.5%
1 120
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26088
99.5%
1 120
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26088
99.5%
1 120
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26088
99.5%
1 120
 
0.5%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.156202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.191032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.230527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.263876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.305460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.338856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.378270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.413208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.452444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.485611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.526234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.704889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.743761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.778270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.817658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.850688image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.891016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.924194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:35.963162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:35.997985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:36.037253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.070662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24618 
1
 
1590

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Length

2025-05-14T19:18:36.111967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.147549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Most occurring characters

ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25493 
1
 
715

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25493
97.3%
1 715
 
2.7%

Length

2025-05-14T19:18:36.189911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.227364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25493
97.3%
1 715
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 25493
97.3%
1 715
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25493
97.3%
1 715
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25493
97.3%
1 715
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25493
97.3%
1 715
 
2.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24898 
1
 
1310

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Length

2025-05-14T19:18:36.269397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.305001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25157 
1
 
1051

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25157
96.0%
1 1051
 
4.0%

Length

2025-05-14T19:18:36.349033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.384490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25157
96.0%
1 1051
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25157
96.0%
1 1051
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25157
96.0%
1 1051
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25157
96.0%
1 1051
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25157
96.0%
1 1051
 
4.0%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24463 
1
 
1745

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24463
93.3%
1 1745
 
6.7%

Length

2025-05-14T19:18:36.426627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.463996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24463
93.3%
1 1745
 
6.7%

Most occurring characters

ValueCountFrequency (%)
0 24463
93.3%
1 1745
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24463
93.3%
1 1745
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24463
93.3%
1 1745
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24463
93.3%
1 1745
 
6.7%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24056 
1
 
2152

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24056
91.8%
1 2152
 
8.2%

Length

2025-05-14T19:18:36.507008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.543123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24056
91.8%
1 2152
 
8.2%

Most occurring characters

ValueCountFrequency (%)
0 24056
91.8%
1 2152
 
8.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24056
91.8%
1 2152
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24056
91.8%
1 2152
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24056
91.8%
1 2152
 
8.2%

Production LatestAverage Reactive Power Gen 2 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23782 
1
2426 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Length

2025-05-14T19:18:36.589856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.626258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Most occurring characters

ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23782
90.7%
1 2426
 
9.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22350 
1
3858 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22350
85.3%
1 3858
 
14.7%

Length

2025-05-14T19:18:36.670349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.708533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22350
85.3%
1 3858
 
14.7%

Most occurring characters

ValueCountFrequency (%)
0 22350
85.3%
1 3858
 
14.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22350
85.3%
1 3858
 
14.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22350
85.3%
1 3858
 
14.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22350
85.3%
1 3858
 
14.7%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:36.752807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.785931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:36.826996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.860341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:36.899423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:36.934185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total Active power [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-14T19:18:36.973444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:37.009026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26118 
1
 
90

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26118
99.7%
1 90
 
0.3%

Length

2025-05-14T19:18:37.054238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:37.090460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26118
99.7%
1 90
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26118
99.7%
1 90
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26118
99.7%
1 90
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26118
99.7%
1 90
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26118
99.7%
1 90
 
0.3%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:37.132383image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:37.167222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:18:37.206301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:37.239312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26056 
1
 
152

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Length

2025-05-14T19:18:37.281738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:18:37.317766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26056
99.4%
1 152
 
0.6%

Correlations

2025-05-14T19:18:37.442398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power limit [W]Active power limit sourceAmbient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Power factor set pointPower factor set point sourceProduction LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Reactive power generator 0,Total accumulated [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]Total Active power [W]Total reactive power [var]
Active power limit [W]1.0000.2370.0000.0000.0000.0000.0000.0300.0000.0000.0000.0000.0200.0290.0090.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0020.0000.0000.0000.0000.0330.0350.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0150.0040.0050.0180.0140.0000.0000.0000.0000.0000.0010.0000.0000.0000.0050.1110.0540.0000.0000.0810.5480.0060.0950.0680.0230.0000.0000.0000.2370.2370.0040.0000.0000.0160.0000.0000.0000.0000.0330.0000.0030.0050.0000.0000.0000.024
Active power limit source0.2371.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0960.0000.0000.0000.0000.3060.0000.0600.0000.0000.0000.0000.0000.7500.7500.0000.0000.0000.0020.0000.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.027
Ambient Temp. Avg. [°C]0.0000.0001.0000.0000.0320.0230.0000.0130.0070.0290.0200.0030.0020.0170.0000.0160.0000.0000.0140.0130.0210.0120.0160.0000.0080.0120.0000.0010.0180.0000.0160.0120.0160.0000.0070.0060.0310.0140.0000.0070.0160.0190.0140.0000.0150.0160.0100.0000.0160.0130.0070.0070.0220.0080.0090.0240.0000.0000.0010.0070.0000.0170.0070.0050.0120.0070.0180.0210.0140.0140.0110.0000.0200.0120.0150.0130.0100.0330.0320.0000.0000.0160.0220.0000.0130.0000.0140.0200.0100.0000.0050.0070.0000.0070.0210.0000.000
Ambient WindDir Absolute Avg. [°]0.0000.0000.0001.0000.1150.0000.0190.0000.0170.0100.0250.0000.0000.0000.0100.0060.0040.0000.0000.0030.0070.0000.0000.0090.0000.0150.0000.0000.0150.0000.0000.0060.0320.0410.0140.0220.0100.0000.0050.0240.0130.0240.0040.0000.0000.0090.0000.0000.0000.0160.0000.0120.0230.0100.0160.0170.0170.0040.0180.0020.0080.0000.0170.0080.0060.0000.0070.0000.0060.0250.0000.0000.0060.0000.0000.0130.0140.0070.0000.0000.0000.0280.0000.0050.0290.0220.0160.0000.0000.0000.0290.0380.0040.0250.0240.0050.005
Ambient WindDir Relative Avg. [°]0.0000.0000.0320.1151.0000.0000.0170.0000.0160.0750.1130.0500.0250.0000.0240.0000.0240.0000.0000.0000.0150.0070.0000.0260.0090.0750.0080.0030.0100.0180.0140.0120.0750.1070.0640.0350.0150.0030.0000.0640.0160.0180.0170.0000.0180.0030.0100.0110.0190.0000.0120.0130.0790.0550.0450.0270.0000.0000.0000.0040.0060.0000.0110.0000.0000.0000.0500.0430.0000.0690.0200.0000.0520.0260.0270.0180.0130.0010.0210.0000.0000.0920.0060.0050.1100.0200.0270.0180.0530.0000.0820.0880.0530.0310.0340.0000.018
Ambient WindSpeed Avg. [m/s]0.0000.0000.0230.0000.0001.0000.1470.1140.0180.1210.0400.0570.0570.0000.0000.0000.0000.0000.0000.0940.0620.0630.0870.0620.0780.0130.0040.0100.0000.0260.0400.0460.1200.0620.0920.0520.0000.0000.0300.0210.2000.1930.1990.0000.2450.1130.1110.0690.2100.1030.0990.0620.0320.0450.0410.0330.0000.0000.0000.0320.0260.0310.0070.0000.0000.0000.0010.0130.0250.0460.0160.0000.0030.0200.0000.0440.0160.0060.0050.0000.0000.0310.1100.1030.0250.0000.0100.2210.0240.0000.1230.0600.0810.0490.0160.0000.000
Ambient WindSpeed Max. [m/s]0.0000.0000.0000.0190.0170.1471.0000.0220.0380.0730.0440.0410.0400.0000.0100.0030.0000.0000.0090.0630.0470.0490.0670.0350.0430.0130.0070.0000.0270.0240.0400.0220.0710.0640.0520.0430.0070.0000.0290.0290.1100.1140.1200.0000.1090.1250.0580.0880.1120.1200.0550.0790.0410.0470.0410.0400.0000.0000.0000.0270.0260.0220.0050.0070.0000.0000.0000.0000.0170.0420.0000.0000.0000.0000.0000.0370.0220.0000.0050.0000.0000.0400.0540.0590.0360.0080.0140.1230.0330.0000.0670.0660.0390.0460.0140.0000.000
Ambient WindSpeed Min. [m/s]0.0300.0000.0130.0000.0000.1140.0221.0000.0260.0900.0270.1120.0820.0000.0000.0000.0000.0000.0110.0380.0100.0240.0320.0200.0320.0000.0000.0000.0040.0030.0110.0060.0840.0620.1350.0590.0110.0000.0040.0440.0850.0820.0880.0000.0840.0340.1160.0490.0820.0360.1070.0510.0710.0810.0730.0670.0070.0050.0050.0180.0190.0260.0080.0000.0040.0070.0280.0330.0460.0770.0300.0280.0300.0130.0230.0530.0120.0040.0000.0000.0000.0530.0340.0770.0460.0230.0570.0820.0630.0000.0790.0490.1180.0410.0220.0000.000
Ambient WindSpeed StdDev [m/s]0.0000.0000.0070.0170.0160.0180.0380.0261.0000.0510.0000.0420.0710.0000.0000.0020.0000.0000.0070.0140.0100.0120.0140.0100.0170.0000.0000.0000.0000.0180.0220.0220.0180.0270.0140.0670.0150.0050.0210.0310.0450.0420.0400.0000.0400.0340.0300.1460.0280.0350.0180.1280.0420.0370.0310.0400.0110.0040.0000.0250.0240.0200.0090.0000.0020.0000.0080.0100.0070.0180.0000.0030.0100.0000.0000.0250.0490.0130.0000.0000.0000.0170.0080.0170.0280.0000.0210.0300.0220.0000.0170.0210.0140.0510.0100.0000.000
Blades PitchAngle Avg. [°]0.0000.0000.0290.0100.0750.1210.0730.0900.0511.0000.3020.4490.4710.0000.0250.0160.0180.0180.0150.0550.0610.0690.1180.1550.0740.0840.0070.0000.0280.0150.0250.0160.2700.2410.2540.2510.0630.0310.0230.3010.1690.1820.2020.0000.2480.2510.2370.3280.2350.2280.1750.2810.4270.3240.2510.2800.0040.0000.0000.0360.0400.0390.0140.0290.0170.0000.1610.1140.1430.4220.0380.0000.1570.0490.0570.1000.1130.0140.0110.0000.0000.3870.0770.2850.3630.0940.2720.2400.3420.0200.2860.2150.2190.2170.0510.0000.033
Blades PitchAngle Max. [°]0.0000.0000.0200.0250.1130.0400.0440.0270.0000.3021.0000.1520.1230.0150.0280.0000.0090.0340.0050.0350.0330.0270.0720.0800.0410.1050.0000.0140.0000.0000.0030.0090.1210.2920.0890.0810.0430.0000.0000.2440.1070.1150.1320.0060.1720.2020.1410.2300.1470.1770.0940.1660.1970.1950.0930.1000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0940.0830.0340.2170.0280.0040.0960.0340.0310.1720.0680.0050.0160.0000.0000.2640.0300.1390.2640.0550.0890.1520.1410.0180.1330.2520.0790.0790.0380.0000.007
Blades PitchAngle Min. [°]0.0000.0000.0030.0000.0500.0570.0410.1120.0420.4490.1521.0000.5650.0020.0400.0000.0260.0000.0070.0570.0570.0600.0810.1320.0480.0200.0000.0000.0120.0000.0000.0000.2270.1510.3740.2420.0390.0150.0110.3490.1230.1320.1460.0000.1840.1600.1820.2300.1790.1460.1490.2230.6310.5170.3660.4640.0000.0130.0000.0200.0260.0280.0080.0320.0240.0130.1110.0800.2910.5430.0430.0000.1160.0440.0810.1160.0550.0030.0000.0000.0000.4280.1870.2910.4000.2080.4470.1930.4880.0210.2410.1290.3200.2030.0550.0000.034
Blades PitchAngle StdDev [°]0.0200.0000.0020.0000.0250.0570.0400.0820.0710.4710.1230.5651.0000.0080.0290.0000.0120.0240.0050.0170.0320.0330.0430.0840.0280.0480.0000.0120.0160.0070.0000.0000.1880.1640.2640.4150.0570.0160.0060.3160.1300.1400.1570.0000.2130.2070.2850.2830.1900.1740.1980.2770.5120.4100.2920.4780.0000.0000.0050.0220.0260.0370.0190.0270.0340.0130.1180.0830.2230.4500.0370.0200.1140.0350.0770.1020.1290.0000.0000.0000.0000.3550.1430.2920.3350.1800.5110.1980.3970.0650.2000.1450.2120.3500.0310.0000.079
Controller Ground Temp. Avg. [°C]0.0290.0000.0170.0000.0000.0000.0000.0000.0000.0000.0150.0020.0081.0000.0000.0000.0000.0170.0000.0010.0040.0000.0110.0000.0110.0000.0120.0000.0000.0140.0170.0080.0060.0080.0000.0000.0020.0060.0000.0030.0000.0100.0070.0000.0000.0110.0000.0000.0000.0100.0070.0000.0040.0040.0000.0040.0000.0000.0100.0000.0000.0000.0000.0050.0000.0110.0000.0000.0000.0090.0000.0400.0000.0000.0110.0000.0000.0010.0130.0000.0000.0050.0000.0000.0100.0080.0050.0000.0110.0000.0000.0070.0000.0000.0000.0000.000
Controller Hub Temp. Avg. [°C]0.0090.0000.0000.0100.0240.0000.0100.0000.0000.0250.0280.0400.0290.0001.0000.0000.0100.0000.0000.0000.0090.0000.0120.0120.0110.0230.0000.0150.0000.0040.0000.0000.0380.0450.0280.0380.0060.0000.0000.0380.0320.0290.0310.0000.0400.0340.0320.0320.0380.0400.0330.0380.0430.0190.0280.0400.0000.0000.0000.0000.0040.0060.0060.0000.0000.0000.0180.0230.0280.0550.0180.0160.0140.0190.0200.0070.0250.0000.0120.0000.0000.0490.0050.0480.0440.0100.0300.0370.0220.0000.0390.0330.0130.0310.0510.0000.000
Controller Top Temp. Avg. [°C]0.0000.0000.0160.0060.0000.0000.0030.0000.0020.0160.0000.0000.0000.0000.0001.0000.0000.0370.0000.0000.0000.0000.0000.0110.0000.0240.0000.0250.0000.0040.0050.0070.0070.0000.0060.0000.0000.0050.0000.0000.0000.0070.0000.0000.0000.0130.0020.0070.0000.0070.0050.0130.0090.0000.0040.0010.0060.0000.0000.0000.0000.0000.0000.0180.0220.0090.0080.0040.0000.0000.0000.0000.0090.0000.0170.0000.0000.0130.0950.0000.0000.0000.0000.0000.0000.0210.0000.0000.0150.0000.0130.0000.0070.0000.0090.0000.000
Controller VCP ChokecoilTemp. Avg. [°C]0.0000.0000.0000.0040.0240.0000.0000.0000.0000.0180.0090.0260.0120.0000.0100.0001.0000.0000.0310.0140.0240.0140.0350.0360.0070.0210.0560.0590.0290.0460.0450.0450.0150.0230.0030.0410.0120.0250.0220.0380.0320.0310.0280.0000.0180.0150.0200.0000.0190.0180.0350.0000.0000.0190.0050.0020.0000.0000.0000.0260.0330.0260.0020.0350.0230.0380.0110.0120.0540.0030.0000.0000.0100.0010.0030.0070.0110.0000.0120.0000.0000.0370.0610.0080.0390.0540.0050.0120.0230.0110.0200.0190.0000.0380.0040.0000.013
Controller VCP Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0340.0000.0240.0170.0000.0370.0001.0000.0120.0090.0170.0160.0200.0070.0050.0140.0000.0090.0160.0000.0080.0070.0120.0210.0100.0250.0880.0370.0000.0160.0140.0140.0180.0000.0210.0250.0320.0230.0200.0340.0210.0330.0110.0000.0000.0330.0000.0000.0000.0000.0000.0130.0090.0190.0290.0000.0070.0100.0120.0180.0080.0000.0060.0050.0030.0000.0120.0060.0690.0000.0000.0190.0030.0190.0200.0000.0310.0240.0170.0000.0110.0210.0030.0360.0140.0000.000
Controller VCP WaterTemp. Avg. [°C]0.0000.0000.0140.0000.0000.0000.0090.0110.0070.0150.0050.0070.0050.0000.0000.0000.0310.0121.0000.0520.0500.0230.0580.0350.0320.0000.0480.0420.2760.0780.0790.0520.0080.0000.0090.0110.0270.0160.1440.0190.0210.0170.0200.0110.0000.0000.0000.0000.0130.0000.0070.0000.0060.0000.0000.0000.0110.0000.0000.2600.2880.2610.0200.0250.0280.0060.0000.0110.0150.0000.0000.0000.0000.0000.0000.0160.0110.0300.0140.0000.0000.0100.0000.0070.0240.0030.0000.0150.0090.0000.0050.0100.0070.0100.0000.0000.000
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0000.0000.0130.0030.0000.0940.0630.0380.0140.0550.0350.0570.0170.0010.0000.0000.0140.0090.0521.0000.3100.2520.3100.1590.2690.0190.0720.0510.0320.0790.0980.1020.1440.0540.0720.0780.0300.0200.0640.0410.0700.0730.0820.0000.0860.0690.0540.0620.0870.0620.0330.0550.0280.0350.0380.0340.0000.0000.0060.0850.0690.0650.0000.0000.0020.0000.0230.0110.0000.0350.0060.0000.0250.0020.0000.0110.0210.0180.0060.0000.0000.0580.0440.0170.0550.0000.0000.0930.0300.0000.1270.0620.0920.0850.0060.0000.000
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0000.0210.0070.0150.0620.0470.0100.0100.0610.0330.0570.0320.0040.0090.0000.0240.0170.0500.3101.0000.1530.2160.1780.2510.0190.0800.0580.0310.1000.1110.1140.1620.0820.0980.0940.0350.0220.0530.0540.0600.0670.0740.0000.0700.0660.0510.0460.0710.0640.0250.0440.0540.0520.0590.0510.0050.0070.0070.0720.0560.0640.0070.0000.0210.0000.0130.0030.0000.0620.0000.0000.0150.0000.0020.0050.0080.0200.0060.0000.0000.0820.0410.0000.0890.0240.0270.0710.0370.0000.1800.0780.1040.1070.0220.0000.000
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0000.0000.0120.0000.0070.0630.0490.0240.0120.0690.0270.0600.0330.0000.0000.0000.0140.0160.0230.2520.1531.0000.1870.1950.2630.0720.0250.0000.0140.0390.0420.0560.1560.0640.0940.1150.0270.0160.0320.0350.0850.0850.0910.0160.0860.0980.0630.0750.0930.0960.0450.0740.0420.0430.0550.0410.0000.0000.0000.0230.0340.0230.0050.0080.0000.0110.0310.0170.0200.0520.0000.0000.0330.0000.0130.0300.0360.0000.0040.0000.0000.0600.0380.0620.0590.0000.0050.1000.0380.0000.1460.0750.0900.0840.0160.0000.000
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0000.0000.0160.0000.0000.0870.0670.0320.0140.1180.0720.0810.0430.0110.0120.0000.0350.0200.0580.3100.2160.1871.0000.2640.1930.0260.0870.0700.0370.1060.1010.1210.1820.0820.1100.0970.0370.0210.0570.0530.0680.0610.0720.0000.0760.0750.0510.0650.0780.0610.0310.0580.0470.0480.0580.0460.0000.0070.0000.0730.0660.0610.0000.0000.0020.0040.0290.0170.0000.0670.0000.0000.0290.0080.0190.0210.0160.0110.0000.0000.0000.0800.0530.0210.0750.0000.0000.0850.0480.0000.1580.0890.1170.0870.0160.0000.000
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0030.0000.0000.0090.0260.0620.0350.0200.0100.1550.0800.1320.0840.0000.0120.0110.0360.0070.0350.1590.1780.1950.2641.0000.2050.0760.0680.0720.0380.0610.0610.0550.1960.0960.1960.1040.0450.0200.0270.1030.0440.0470.0540.0000.0590.0670.0570.0660.0570.0550.0210.0540.1160.0920.1210.0850.0020.0000.0000.0440.0390.0410.0000.0250.0230.0350.0320.0270.0740.1580.0060.0000.0360.0090.0190.0580.0220.0000.0000.0000.0000.1390.0930.0340.1280.0230.0490.0620.1100.0000.2030.0980.1830.0910.0370.0000.000
Gear Oil TemperatureBasis Avg. [°C]0.0000.0000.0080.0000.0090.0780.0430.0320.0170.0740.0410.0480.0280.0110.0110.0000.0070.0050.0320.2690.2510.2630.1930.2051.0000.0990.0770.0510.0260.0830.0910.0900.1530.0960.0590.1010.0290.0200.0380.0590.0720.0780.0750.0000.0800.0630.0520.0630.0690.0570.0360.0540.0360.0480.0390.0300.0000.0000.0000.0510.0520.0450.0000.0070.0000.0000.0100.0150.0090.0450.0000.0000.0120.0000.0000.0250.0260.0000.0000.0000.0000.0600.0190.0330.0590.0070.0190.0730.0310.0000.1500.1100.0680.0980.0110.0000.007
Gear Oil TemperatureLevel1 Avg. [°C]0.0020.0000.0120.0150.0750.0130.0130.0000.0000.0840.1050.0200.0480.0000.0230.0240.0210.0140.0000.0190.0190.0720.0260.0760.0991.0000.0090.0060.0070.0000.0000.0000.0590.1270.0350.0650.0560.0310.0060.0190.0370.0390.0520.0000.0500.0490.0510.0510.0600.0470.0550.0390.0450.0360.0410.0510.0000.0080.0150.0000.0000.0060.0000.0150.0000.0000.0180.0150.0100.0480.0160.0000.0200.0190.0220.0340.0390.0090.0200.0000.0000.0560.0350.0240.0630.0270.0240.0600.0550.0000.0670.1250.0130.0800.0210.0000.000
Generator Bearing Temp. Avg. [°C]0.0000.0000.0000.0000.0080.0040.0070.0000.0000.0070.0000.0000.0000.0120.0000.0000.0560.0000.0480.0720.0800.0250.0870.0680.0770.0091.0000.2100.0500.1090.1070.1020.0270.0000.0070.0000.0040.0210.0270.0070.0070.0050.0000.0000.0000.0000.0100.0040.0070.0000.0140.0090.0000.0000.0190.0000.0000.0000.0000.0560.0440.0360.0000.0520.0220.0180.0000.0000.0040.0050.0080.0000.0000.0050.0080.0140.0090.0190.0040.0000.0000.0000.0140.0160.0000.0000.0040.0000.0000.0000.0190.0110.0220.0000.0050.0000.004
Generator Bearing2 Temp. Avg. [°C]0.0000.0000.0010.0000.0030.0100.0000.0000.0000.0000.0140.0000.0120.0000.0150.0250.0590.0090.0420.0510.0580.0000.0700.0720.0510.0060.2101.0000.0520.0780.0870.0670.0140.0160.0140.0160.0120.0210.0100.0070.0140.0110.0140.0100.0140.0000.0140.0000.0130.0030.0180.0000.0130.0000.0000.0130.0000.0000.0000.0330.0470.0240.0040.0440.0260.0420.0000.0040.0000.0080.0040.0000.0050.0000.0030.0060.0080.0170.0490.0000.0000.0090.0150.0230.0030.0000.0170.0030.0040.0000.0150.0000.0240.0140.0070.0000.010
Generator CoolingWater Temp. Avg. [°C]0.0000.0000.0180.0150.0100.0000.0270.0040.0000.0280.0000.0120.0160.0000.0000.0000.0290.0160.2760.0320.0310.0140.0370.0380.0260.0070.0500.0521.0000.0620.0620.0500.0180.0080.0160.0150.0310.0390.1060.0180.0100.0080.0080.0000.0000.0000.0000.0040.0080.0040.0000.0000.0110.0110.0110.0000.0000.0000.0000.1720.1940.1890.0210.0240.0220.0270.0000.0090.0030.0170.0000.0000.0000.0000.0000.0090.0000.0250.0150.0000.0000.0250.0000.0000.0260.0000.0070.0090.0250.0000.0180.0130.0100.0100.0020.0000.000
Generator Phase1 Temp. Avg. [°C]0.0000.0070.0000.0000.0180.0260.0240.0030.0180.0150.0000.0000.0070.0140.0040.0040.0460.0000.0780.0790.1000.0390.1060.0610.0830.0000.1090.0780.0621.0000.4640.3620.0230.0000.0090.0140.0250.0000.0790.0200.0560.0670.0600.0000.0370.0180.0150.0380.0590.0330.0280.0380.0050.0100.0250.0120.0000.0000.0000.0980.0870.0870.0200.0090.0130.0170.0000.0000.0160.0000.0000.0070.0000.0100.0000.0000.0250.0000.0030.0070.0070.0170.0120.0000.0240.0330.0210.0560.0100.0000.0130.0000.0180.0110.0000.0000.000
Generator Phase2 Temp. Avg. [°C]0.0330.0000.0160.0000.0140.0400.0400.0110.0220.0250.0030.0000.0000.0170.0000.0050.0450.0080.0790.0980.1110.0420.1010.0610.0910.0000.1070.0870.0620.4641.0000.3850.0380.0010.0120.0160.0420.0000.0710.0180.0580.0750.0680.0000.0450.0290.0130.0430.0680.0360.0210.0380.0030.0180.0190.0130.0130.0160.0110.0940.0870.0920.0270.0190.0280.0310.0000.0060.0160.0000.0050.0000.0000.0100.0000.0000.0310.0000.0000.0000.0000.0090.0210.0110.0200.0340.0220.0650.0080.0020.0360.0000.0130.0190.0000.0000.013
Generator Phase3 Temp. Avg. [°C]0.0350.0000.0120.0060.0120.0460.0220.0060.0220.0160.0090.0000.0000.0080.0000.0070.0450.0070.0520.1020.1140.0560.1210.0550.0900.0000.1020.0670.0500.3620.3851.0000.0550.0260.0150.0280.0230.0000.0660.0200.0610.0770.0640.0000.0420.0290.0170.0340.0600.0350.0210.0360.0000.0120.0190.0030.0050.0020.0020.0860.0690.0750.0230.0230.0300.0060.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0230.0000.0070.0000.0000.0250.0090.0150.0240.0300.0150.0660.0010.0000.0460.0130.0280.0310.0000.0000.012
Generator RPM Avg. [RPM]0.0000.0000.0160.0320.0750.1200.0710.0840.0180.2700.1210.2270.1880.0060.0380.0070.0150.0120.0080.1440.1620.1560.1820.1960.1530.0590.0270.0140.0180.0230.0380.0551.0000.3750.3650.4540.0420.0130.0080.2070.1650.1740.1780.0000.1830.2060.1620.1940.1900.1880.1130.1740.2330.1700.1880.1670.0000.0080.0040.0440.0390.0440.0110.0000.0220.0060.1170.0930.0320.2560.0260.0000.1220.0300.0570.0430.0630.0000.0120.0000.0000.3090.0550.1270.2990.0000.1310.2030.1960.0130.7640.3500.3370.4020.0530.0000.041
Generator RPM Max. [RPM]0.0000.0000.0000.0410.1070.0620.0640.0620.0270.2410.2920.1510.1640.0080.0450.0000.0230.0210.0000.0540.0820.0640.0820.0960.0960.1270.0000.0160.0080.0000.0010.0260.3751.0000.1400.2970.0490.0140.0000.1520.1310.1370.1420.0070.1550.2040.1670.1990.1370.1930.1180.1580.1960.1780.1030.1090.0000.0000.0030.0180.0180.0190.0250.0070.0200.0140.0770.0770.0660.2200.0110.0000.0810.0140.0200.0320.0680.0190.0000.0000.0000.2100.0000.1830.2220.0340.1310.1470.1360.0000.3260.7780.1160.2440.0690.0000.000
Generator RPM Min. [RPM]0.0030.0000.0070.0140.0640.0920.0520.1350.0140.2540.0890.3740.2640.0000.0280.0060.0030.0100.0090.0720.0980.0940.1100.1960.0590.0350.0070.0140.0160.0090.0120.0150.3650.1401.0000.2360.0490.0300.0000.2690.1300.1280.1440.0000.1450.1020.1530.0960.1570.0840.1540.0940.3330.2880.3100.2560.0000.0100.0000.0220.0340.0380.0080.0170.0280.0100.0780.0480.1850.4250.0200.0000.0820.0210.0530.1240.0500.0000.0080.0000.0000.3850.1580.1720.3510.0240.2600.1670.2680.0350.3910.1270.7840.2060.0470.0000.040
Generator RPM StdDev [RPM]0.0000.0000.0060.0220.0350.0520.0430.0590.0670.2510.0810.2420.4150.0000.0380.0000.0410.0250.0110.0780.0940.1150.0970.1040.1010.0650.0000.0160.0150.0140.0160.0280.4540.2970.2361.0000.0470.0120.0120.2440.1460.1520.1580.0000.1800.2100.2640.2520.1730.1890.2020.2530.2170.1740.1700.3040.0000.0000.0000.0290.0220.0370.0100.0000.0180.0000.1030.0710.0060.2380.0220.0000.1050.0190.0890.0540.1330.0000.0080.0000.0000.2740.0120.1770.2600.0000.2970.1840.1580.0430.4210.2570.2070.7300.0370.0000.056
Generator SlipRing Temp. Avg. [°C]0.0000.0000.0310.0100.0150.0000.0070.0110.0150.0630.0430.0390.0570.0020.0060.0000.0120.0880.0270.0300.0350.0270.0370.0450.0290.0560.0040.0120.0310.0250.0420.0230.0420.0490.0490.0471.0000.0450.0180.0360.0450.0470.0450.0040.0380.0320.0490.0450.0400.0320.0410.0350.0490.0320.0350.0560.0000.0050.0100.0270.0170.0200.0260.0220.0300.0080.0000.0080.0170.0600.0060.0000.0000.0000.0000.0240.0210.0180.0460.0000.0000.0480.0190.0390.0630.0000.0510.0410.0400.0000.0390.0440.0430.0420.0100.0000.000
Grid Busbar Temp. Avg. [°C]0.0000.0000.0140.0000.0030.0000.0000.0000.0050.0310.0000.0150.0160.0060.0000.0050.0250.0370.0160.0200.0220.0160.0210.0200.0200.0310.0210.0210.0390.0000.0000.0000.0130.0140.0300.0120.0451.0000.0090.0000.0000.0000.0030.0000.0010.0000.0090.0090.0000.0000.0000.0030.0130.0130.0000.0080.0000.0070.0000.0040.0090.0000.0210.0290.0180.0270.0070.0000.0290.0270.0000.0000.0060.0000.0050.0100.0000.0210.0560.0000.0000.0000.0180.0180.0050.0240.0210.0000.0210.0000.0090.0200.0150.0050.0000.0000.000
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0000.0000.0050.0000.0300.0290.0040.0210.0230.0000.0110.0060.0000.0000.0000.0220.0000.1440.0640.0530.0320.0570.0270.0380.0060.0270.0100.1060.0790.0710.0660.0080.0000.0000.0120.0180.0091.0000.0110.0610.0600.0740.0000.0460.0310.0100.0350.0610.0370.0240.0320.0150.0090.0150.0170.0000.0000.0000.2260.2040.2300.0150.0090.0050.0120.0230.0170.0000.0000.0000.0000.0240.0000.0110.0000.0000.0120.0000.0000.0000.0200.0330.0050.0220.0170.0210.0620.0000.0080.0000.0000.0070.0160.0030.0000.012
Grid Production CosPhi Avg.0.0000.0000.0070.0240.0640.0210.0290.0440.0310.3010.2440.3490.3160.0030.0380.0000.0380.0160.0190.0410.0540.0350.0530.1030.0590.0190.0070.0070.0180.0200.0180.0200.2070.1520.2690.2440.0360.0000.0111.0000.2190.2170.2400.0100.2190.2350.2310.2530.2810.2700.2300.2680.4630.3570.2500.3340.0000.0110.0000.0190.0190.0430.0130.0000.0120.0000.0940.0960.0170.4820.0400.0000.0960.0370.0360.2200.1230.0130.0100.0000.0000.6090.0200.2370.5730.0630.3780.2810.3490.0350.2170.1290.2150.2010.0630.0000.048
Grid Production CurrentPhase1 Avg. [A]0.0000.0000.0160.0130.0160.2000.1100.0850.0450.1690.1070.1230.1300.0000.0320.0000.0320.0140.0210.0700.0600.0850.0680.0440.0720.0370.0070.0140.0100.0560.0580.0610.1650.1310.1300.1460.0450.0000.0610.2191.0000.7490.7480.0010.5370.3000.2920.2950.6600.3370.3770.3260.2010.1620.1360.1590.0170.0130.0070.0520.0450.0490.0130.0000.0190.0000.1040.0750.0470.1530.0130.0050.1020.0070.0450.1880.1250.0000.0070.0000.0000.2570.1640.3550.2390.0070.0770.6280.1440.0000.1720.1050.1080.1210.0470.0000.009
Grid Production CurrentPhase2 Avg. [A]0.0000.0000.0190.0240.0180.1930.1140.0820.0420.1820.1150.1320.1400.0100.0290.0070.0310.0140.0170.0730.0670.0850.0610.0470.0780.0390.0050.0110.0080.0670.0750.0770.1740.1370.1280.1520.0470.0000.0600.2170.7491.0000.7500.0060.5520.3180.2980.3210.6520.3480.3650.3420.2300.1800.1550.1790.0120.0100.0000.0480.0440.0530.0170.0000.0160.0000.0990.0700.0490.1720.0000.0000.0970.0000.0340.1740.1360.0000.0050.0000.0000.2530.1680.3780.2620.0090.0850.6310.1630.0000.1760.1090.1050.1350.0480.0000.009
Grid Production CurrentPhase3 Avg. [A]0.0000.0000.0140.0040.0170.1990.1200.0880.0400.2020.1320.1460.1570.0070.0310.0000.0280.0180.0200.0820.0740.0910.0720.0540.0750.0520.0000.0140.0080.0600.0680.0640.1780.1420.1440.1580.0450.0030.0740.2400.7480.7501.0000.0050.5840.3380.3120.3420.7020.3680.3870.3670.2270.1890.1460.1760.0190.0190.0110.0480.0500.0580.0190.0040.0130.0000.1080.0820.0520.1930.0190.0060.1060.0140.0470.1580.1350.0000.0110.0000.0000.2900.1710.4050.2590.0010.0950.6790.1630.0000.1820.1140.1210.1330.0490.0000.008
Grid Production Frequency Avg. [Hz]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0160.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0070.0000.0000.0040.0000.0000.0100.0010.0060.0051.0000.0040.0000.0000.0000.0080.0030.0040.0020.0060.0050.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0060.0000.0060.0000.0000.0070.0000.0030.0090.0010.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.000
Grid Production PossiblePower Avg. [W]0.0000.0000.0150.0000.0180.2450.1090.0840.0400.2480.1720.1840.2130.0000.0400.0000.0180.0210.0000.0860.0700.0860.0760.0590.0800.0500.0000.0140.0000.0370.0450.0420.1830.1550.1450.1800.0380.0010.0460.2190.5370.5520.5840.0041.0000.4450.4580.4520.6500.3720.3290.3930.1740.1880.1050.1590.0050.0130.0000.0340.0290.0490.0000.0130.0230.0000.0710.0800.0560.2420.0090.0000.0740.0140.0330.1500.1200.0150.0050.0000.0000.2290.2110.4480.1940.0170.1410.6330.1290.0000.1870.1340.1240.1600.0440.0000.007
Grid Production PossiblePower Max. [W]0.0000.0000.0160.0090.0030.1130.1250.0340.0340.2510.2020.1600.2070.0110.0340.0130.0150.0250.0000.0690.0660.0980.0750.0670.0630.0490.0000.0000.0000.0180.0290.0290.2060.2040.1020.2100.0320.0000.0310.2350.3000.3180.3380.0000.4451.0000.3390.4620.3690.7090.2590.3810.1910.1770.0800.1740.0000.0040.0000.0210.0160.0350.0000.0000.0030.0000.0820.0990.0510.2380.0000.0000.0860.0000.0110.0800.1150.0210.0130.0000.0000.2230.0910.3200.2070.0000.1480.3830.1380.0020.2090.1840.0820.2020.0310.0000.006
Grid Production PossiblePower Min. [W]0.0000.0000.0100.0000.0100.1110.0580.1160.0300.2370.1410.1820.2850.0000.0320.0020.0200.0320.0000.0540.0510.0630.0510.0570.0520.0510.0100.0140.0000.0150.0130.0170.1620.1670.1530.2640.0490.0090.0100.2310.2920.2980.3120.0000.4580.3391.0000.3350.3490.3120.5140.3170.1770.1550.1060.2180.0000.0070.0000.0140.0180.0350.0100.0210.0140.0070.0530.0450.0530.2330.0000.0000.0490.0000.0000.1020.1360.0000.0000.0000.0000.2080.0930.3220.1910.0000.2630.3610.1330.0110.1670.1420.1360.2290.0360.0000.012
Grid Production PossiblePower StdDev [W]0.0000.0000.0000.0000.0110.0690.0880.0490.1460.3280.2300.2300.2830.0000.0320.0070.0000.0230.0000.0620.0460.0750.0650.0660.0630.0510.0040.0000.0040.0380.0430.0340.1940.1990.0960.2520.0450.0090.0350.2530.2950.3210.3420.0000.4520.4620.3351.0000.3810.4030.2670.7240.2380.2330.1270.1970.0000.0000.0000.0250.0410.0360.0080.0100.0150.0070.0730.0790.0610.2910.0000.0000.0760.0000.0000.0790.1530.0110.0020.0000.0000.2530.0930.3570.2370.0390.1810.3880.1900.0000.1880.1780.0790.2280.0330.0000.005
Grid Production Power Avg. [W]0.0100.0000.0160.0000.0190.2100.1120.0820.0280.2350.1470.1790.1900.0000.0380.0000.0190.0200.0130.0870.0710.0930.0780.0570.0690.0600.0070.0130.0080.0590.0680.0600.1900.1370.1570.1730.0400.0000.0610.2810.6600.6520.7020.0080.6500.3690.3490.3811.0000.4350.4420.4430.2290.1780.1470.1830.0130.0130.0110.0450.0460.0560.0090.0120.0200.0000.1080.0840.0530.2300.0150.0060.1090.0150.0480.1430.1450.0060.0200.0000.0000.3500.2310.4610.2700.0000.1410.8570.1760.0000.1830.1110.1270.1550.0470.0000.000
Grid Production Power Max. [W]0.0000.0000.0130.0160.0000.1030.1200.0360.0350.2280.1770.1460.1740.0100.0400.0070.0180.0340.0000.0620.0640.0960.0610.0550.0570.0470.0000.0030.0040.0330.0360.0350.1880.1930.0840.1890.0320.0000.0370.2700.3370.3480.3680.0030.3720.7090.3120.4030.4351.0000.2830.4100.1980.1840.0830.1560.0000.0050.0000.0240.0120.0440.0090.0000.0000.0100.0770.0950.0270.2360.0120.0000.0800.0120.0210.0710.1020.0230.0200.0000.0000.2460.0610.3310.2280.0180.1340.4260.1420.0060.1890.1630.0680.1820.0370.0000.007
Grid Production Power Min. [W]0.0000.0000.0070.0000.0120.0990.0550.1070.0180.1750.0940.1490.1980.0070.0330.0050.0350.0210.0070.0330.0250.0450.0310.0210.0360.0550.0140.0180.0000.0280.0210.0210.1130.1180.1540.2020.0410.0000.0240.2300.3770.3650.3870.0040.3290.2590.5140.2670.4420.2831.0000.3060.1720.1300.1480.1830.0000.0030.0000.0200.0180.0350.0140.0000.0120.0000.0480.0290.0300.1730.0020.0000.0480.0000.0240.0990.1710.0000.0070.0000.0000.2120.0830.3100.1870.0250.2130.4240.1110.0090.1140.0910.1330.1810.0410.0000.012
Grid Production Power StdDev [W]0.0150.0000.0070.0120.0130.0620.0790.0510.1280.2810.1660.2230.2770.0000.0380.0130.0000.0330.0000.0550.0440.0740.0580.0540.0540.0390.0090.0000.0000.0380.0380.0360.1740.1580.0940.2530.0350.0030.0320.2680.3260.3420.3670.0020.3930.3810.3170.7240.4430.4100.3061.0000.2490.2170.1360.2220.0000.0030.0000.0220.0360.0310.0120.0050.0060.0000.1260.1150.0790.2720.0260.0050.1260.0340.1020.0800.1350.0000.0160.0000.0000.2720.1210.3420.2410.0720.1800.4420.1960.0000.1680.1390.0730.2220.0510.0000.000
Grid Production ReactivePower Avg. [W]0.0040.0000.0220.0230.0790.0320.0410.0710.0420.4270.1970.6310.5120.0040.0430.0090.0000.0110.0060.0280.0540.0420.0470.1160.0360.0450.0000.0130.0110.0050.0030.0000.2330.1960.3330.2170.0490.0130.0150.4630.2010.2300.2270.0060.1740.1910.1770.2380.2290.1980.1720.2491.0000.6390.4870.5890.0090.0240.0130.0240.0260.0320.0210.0220.0250.0170.1180.0820.3120.6630.0400.0060.1130.0370.0690.1370.1250.0140.0140.0000.0000.6270.1630.3060.7020.2060.5440.2220.7260.0210.2450.1700.2610.1850.0570.0000.058
Grid Production ReactivePower Max. [W]0.0050.0000.0080.0100.0550.0450.0470.0810.0370.3240.1950.5170.4100.0040.0190.0000.0190.0000.0000.0350.0520.0430.0480.0920.0480.0360.0000.0000.0110.0100.0180.0120.1700.1780.2880.1740.0320.0130.0090.3570.1620.1800.1890.0050.1880.1770.1550.2330.1780.1840.1300.2170.6391.0000.4310.4850.0000.0160.0110.0130.0190.0240.0150.0200.0370.0140.0810.0660.2940.5270.0200.0140.0810.0120.0320.1510.1200.0050.0000.0000.0000.4290.1770.2820.4240.1890.4090.1770.4970.0070.1830.1560.2370.1420.0280.0000.025
Grid Production ReactivePower Min. [W]0.0180.0140.0090.0160.0450.0410.0410.0730.0310.2510.0930.3660.2920.0000.0280.0040.0050.0000.0000.0380.0590.0550.0580.1210.0390.0410.0190.0000.0110.0250.0190.0190.1880.1030.3100.1700.0350.0000.0150.2500.1360.1550.1460.0000.1050.0800.1060.1270.1470.0830.1480.1360.4870.4311.0000.4040.0000.0120.0000.0220.0150.0150.0090.0110.0150.0070.0720.0390.2500.4060.0150.0190.0660.0230.0460.0830.2490.0050.0000.0140.0140.3450.1850.1500.3670.1220.3050.1380.3840.0100.2120.0840.2760.1530.0360.0000.022
Grid Production ReactivePower StdDev [W]0.0140.0000.0240.0170.0270.0330.0400.0670.0400.2800.1000.4640.4780.0040.0400.0010.0020.0330.0000.0340.0510.0410.0460.0850.0300.0510.0000.0130.0000.0120.0130.0030.1670.1090.2560.3040.0560.0080.0170.3340.1590.1790.1760.0000.1590.1740.2180.1970.1830.1560.1830.2220.5890.4850.4041.0000.0070.0140.0040.0130.0180.0280.0080.0110.0130.0140.0860.0680.2810.4990.0510.0160.0800.0540.0680.0820.1620.0240.0000.0000.0000.4050.2010.2320.4090.1890.5060.1710.4720.0430.1710.0940.1950.2840.0330.0000.071
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0000.0170.0000.0000.0000.0070.0110.0040.0000.0000.0000.0000.0000.0060.0000.0000.0110.0000.0050.0000.0000.0020.0000.0000.0000.0000.0000.0000.0130.0050.0000.0000.0000.0000.0000.0000.0000.0000.0170.0120.0190.0110.0050.0000.0000.0000.0130.0000.0000.0000.0090.0000.0000.0071.0000.5640.6070.0000.0000.0000.0000.0000.0000.0010.0000.0000.0100.0000.0460.0000.0000.0000.0000.0020.0000.0000.0050.0000.0000.0000.0000.0110.0050.0070.0000.0100.0140.0000.0110.0100.0000.0000.0090.0000.000
Grid Production VoltagePhase2 Avg. [V]0.0000.0000.0000.0040.0000.0000.0000.0050.0040.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0070.0000.0000.0080.0000.0000.0000.0000.0160.0020.0080.0000.0100.0000.0050.0070.0000.0110.0130.0100.0190.0000.0130.0040.0070.0000.0130.0050.0030.0030.0240.0160.0120.0140.5641.0000.6370.0020.0000.0000.0010.0000.0000.0000.0000.0000.0080.0150.0440.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0240.0200.0160.0000.0100.0270.0000.0130.0000.0010.0020.0000.0000.000
Grid Production VoltagePhase3 Avg. [V]0.0000.0000.0010.0180.0000.0000.0000.0050.0000.0000.0000.0000.0050.0100.0000.0000.0000.0000.0000.0060.0070.0000.0000.0000.0000.0150.0000.0000.0000.0000.0110.0020.0040.0030.0000.0000.0100.0000.0000.0000.0070.0000.0110.0000.0000.0000.0000.0000.0110.0000.0000.0000.0130.0110.0000.0040.6070.6371.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0130.0040.0440.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0130.0060.0080.0000.0050.0180.0000.0100.0000.0000.0000.0020.0000.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0000.0070.0020.0040.0320.0270.0180.0250.0360.0000.0200.0220.0000.0000.0000.0260.0000.2600.0850.0720.0230.0730.0440.0510.0000.0560.0330.1720.0980.0940.0860.0440.0180.0220.0290.0270.0040.2260.0190.0520.0480.0480.0000.0340.0210.0140.0250.0450.0240.0200.0220.0240.0130.0220.0130.0000.0020.0001.0000.4100.3070.0250.0110.0000.0000.0080.0000.0020.0130.0090.0000.0100.0060.0000.0070.0090.0050.0000.0000.0000.0360.0100.0000.0340.0160.0000.0460.0040.0060.0360.0280.0300.0350.0000.0000.002
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0000.0000.0080.0060.0260.0260.0190.0240.0400.0000.0260.0260.0000.0040.0000.0330.0000.2880.0690.0560.0340.0660.0390.0520.0000.0440.0470.1940.0870.0870.0690.0390.0180.0340.0220.0170.0090.2040.0190.0450.0440.0500.0000.0290.0160.0180.0410.0460.0120.0180.0360.0260.0190.0150.0180.0000.0000.0000.4101.0000.3410.0310.0120.0030.0010.0110.0000.0000.0260.0040.0000.0110.0060.0000.0160.0050.0180.0000.0000.0000.0370.0080.0050.0350.0150.0000.0390.0150.0000.0370.0190.0330.0220.0100.0000.005
Grid RotorInvPhase3 Temp. Avg. [°C]0.0010.0000.0170.0000.0000.0310.0220.0260.0200.0390.0130.0280.0370.0000.0060.0000.0260.0130.2610.0650.0640.0230.0610.0410.0450.0060.0360.0240.1890.0870.0920.0750.0440.0190.0380.0370.0200.0000.2300.0430.0490.0530.0580.0000.0490.0350.0350.0360.0560.0440.0350.0310.0320.0240.0150.0280.0000.0000.0000.3070.3411.0000.0210.0170.0000.0210.0100.0000.0120.0340.0100.0000.0120.0070.0000.0300.0140.0120.0070.0000.0000.0480.0000.0300.0510.0250.0100.0570.0160.0000.0390.0180.0410.0390.0000.0000.000
HVTrafo AirOutlet Temp. Avg. [°C]0.0000.0000.0070.0170.0110.0070.0050.0080.0090.0140.0000.0080.0190.0000.0060.0000.0020.0090.0200.0000.0070.0050.0000.0000.0000.0000.0000.0040.0210.0200.0270.0230.0110.0250.0080.0100.0260.0210.0150.0130.0130.0170.0190.0000.0000.0000.0100.0080.0090.0090.0140.0120.0210.0150.0090.0080.0000.0010.0060.0250.0310.0211.0000.0150.0140.0000.0000.0000.0090.0120.0000.0000.0000.0090.0090.0000.0080.0000.0210.0000.0000.0050.0000.0180.0170.0000.0070.0090.0000.0000.0000.0070.0050.0050.0090.0000.000
HVTrafo Phase1 Temp. Avg. [°C]0.0000.0000.0050.0080.0000.0000.0070.0000.0000.0290.0000.0320.0270.0050.0000.0180.0350.0190.0250.0000.0000.0080.0000.0250.0070.0150.0520.0440.0240.0090.0190.0230.0000.0070.0170.0000.0220.0290.0090.0000.0000.0000.0040.0000.0130.0000.0210.0100.0120.0000.0000.0050.0220.0200.0110.0110.0000.0000.0000.0110.0120.0170.0151.0000.2210.2450.0000.0000.0430.0380.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0090.0550.0100.0050.0120.0190.0150.0180.0000.0010.0000.0200.0000.0000.0030.000
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0000.0120.0060.0000.0000.0000.0040.0020.0170.0000.0240.0340.0000.0000.0220.0230.0290.0280.0020.0210.0000.0020.0230.0000.0000.0220.0260.0220.0130.0280.0300.0220.0200.0280.0180.0300.0180.0050.0120.0190.0160.0130.0000.0230.0030.0140.0150.0200.0000.0120.0060.0250.0370.0150.0130.0000.0000.0000.0000.0030.0000.0140.2211.0000.2030.0000.0000.0290.0320.0000.0000.0000.0000.0000.0390.0070.0120.0210.0000.0000.0200.0340.0160.0130.0000.0350.0180.0160.0000.0120.0130.0270.0100.0000.0000.000
HVTrafo Phase3 Temp. Avg. [°C]0.0050.0100.0070.0000.0000.0000.0000.0070.0000.0000.0000.0130.0130.0110.0000.0090.0380.0000.0060.0000.0000.0110.0040.0350.0000.0000.0180.0420.0270.0170.0310.0060.0060.0140.0100.0000.0080.0270.0120.0000.0000.0000.0000.0000.0000.0000.0070.0070.0000.0100.0000.0000.0170.0140.0070.0140.0010.0000.0000.0000.0010.0210.0000.2450.2031.0000.0000.0060.0460.0250.0000.0110.0000.0000.0000.0000.0030.0010.0120.0100.0100.0020.0520.0000.0000.0110.0110.0000.0160.0000.0000.0100.0030.0000.0110.0000.000
HourCounters Average AlarmActive Avg. [h]0.1110.0960.0180.0070.0500.0010.0000.0280.0080.1610.0940.1110.1180.0000.0180.0080.0110.0070.0000.0230.0130.0310.0290.0320.0100.0180.0000.0000.0000.0000.0000.0000.1170.0770.0780.1030.0000.0070.0230.0940.1040.0990.1080.0000.0710.0820.0530.0730.1080.0770.0480.1260.1180.0810.0720.0860.0000.0000.0000.0080.0110.0100.0000.0000.0000.0001.0000.6330.1770.0000.2600.1440.9400.3040.4800.0830.0120.0240.0000.0960.0960.1710.1360.0000.1510.0710.0020.1110.0860.0090.1220.0590.0670.0830.0320.0000.012
HourCounters Average AmbientOk Avg. [h]0.0540.0000.0210.0000.0430.0130.0000.0330.0100.1140.0830.0800.0830.0000.0230.0040.0120.0100.0110.0110.0030.0170.0170.0270.0150.0150.0000.0040.0090.0000.0060.0000.0930.0770.0480.0710.0080.0000.0170.0960.0750.0700.0820.0000.0800.0990.0450.0790.0840.0950.0290.1150.0820.0660.0390.0680.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.6331.0000.1170.0000.5070.1580.6810.4880.2890.1250.0110.0120.0000.0000.0000.1180.0900.0000.1060.0570.0000.0770.0550.0000.0910.0640.0400.0590.0290.0000.000
HourCounters Average Gen1 Avg. [h]0.0000.0000.0140.0060.0000.0250.0170.0460.0070.1430.0340.2910.2230.0000.0280.0000.0540.0120.0150.0000.0000.0200.0000.0740.0090.0100.0040.0000.0030.0160.0160.0220.0320.0660.1850.0060.0170.0290.0000.0170.0470.0490.0520.0000.0560.0510.0530.0610.0530.0270.0300.0790.3120.2940.2500.2810.0100.0080.0130.0020.0000.0120.0090.0430.0290.0460.1770.1171.0000.5270.0000.0000.1840.0000.0780.0000.0030.0000.0110.0000.0000.0200.6150.3320.0000.3200.1910.0540.2710.0070.0410.0510.1630.0050.0140.0000.008
HourCounters Average Gen2 Avg. [h]0.0000.0000.0140.0250.0690.0460.0420.0770.0180.4220.2170.5430.4500.0090.0550.0000.0030.0180.0000.0350.0620.0520.0670.1580.0450.0480.0050.0080.0170.0000.0000.0000.2560.2200.4250.2380.0600.0270.0000.4820.1530.1720.1930.0100.2420.2380.2330.2910.2300.2360.1730.2720.6630.5270.4060.4990.0000.0150.0040.0130.0260.0340.0120.0380.0320.0250.0000.0000.5271.0000.0000.0000.0000.0000.0000.1360.1120.0140.0000.0000.0000.6300.2900.4970.5680.1230.5120.2360.5310.0210.2720.1970.3470.2000.0530.0000.044
HourCounters Average GridOk Avg. [h]0.0810.0000.0110.0000.0200.0160.0000.0300.0000.0380.0280.0430.0370.0000.0180.0000.0000.0080.0000.0060.0000.0000.0000.0060.0000.0160.0080.0040.0000.0000.0050.0000.0260.0110.0200.0220.0060.0000.0000.0400.0130.0000.0190.0000.0090.0000.0000.0000.0150.0120.0020.0260.0400.0200.0150.0510.0460.0440.0440.0090.0040.0100.0000.0000.0000.0000.2600.5070.0000.0001.0000.2330.3100.7460.4100.0000.0100.0020.0000.0000.0000.0480.0000.0040.0520.0000.0000.0000.0270.0000.0140.0100.0150.0160.0000.0000.000
HourCounters Average GridOn Avg. [h]0.5480.3060.0000.0000.0000.0000.0000.0280.0030.0000.0040.0000.0200.0400.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0060.0000.0000.0000.0000.0000.0060.0000.0000.0050.0060.0140.0190.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.1440.1580.0000.0000.2331.0000.0940.1230.1960.0490.0000.0000.0000.3060.3060.0000.0000.0000.0180.0000.0000.0070.0060.0440.0000.0000.0000.0000.0000.0000.033
HourCounters Average Run Avg. [h]0.0060.0000.0200.0060.0520.0030.0000.0300.0100.1570.0960.1160.1140.0000.0140.0090.0100.0060.0000.0250.0150.0330.0290.0360.0120.0200.0000.0050.0000.0000.0000.0000.1220.0810.0820.1050.0000.0060.0240.0960.1020.0970.1060.0000.0740.0860.0490.0760.1090.0800.0480.1260.1130.0810.0660.0800.0000.0000.0000.0100.0110.0120.0000.0000.0000.0000.9400.6810.1840.0000.3100.0941.0000.2480.5180.0850.0120.0250.0000.0000.0000.1650.1410.0000.1420.0740.0000.1130.0800.0000.1270.0640.0710.0850.0320.0000.000
HourCounters Average ServiceOn Avg. [h]0.0950.0600.0120.0000.0260.0200.0000.0130.0000.0490.0340.0440.0350.0000.0190.0000.0010.0050.0000.0020.0000.0000.0080.0090.0000.0190.0050.0000.0000.0100.0100.0000.0300.0140.0210.0190.0000.0000.0000.0370.0070.0000.0140.0000.0140.0000.0000.0000.0150.0120.0000.0340.0370.0120.0230.0540.0000.0000.0000.0060.0060.0070.0090.0000.0000.0000.3040.4880.0000.0000.7460.1230.2481.0000.3710.0000.0070.0000.0000.0600.0600.0500.0000.0000.0520.0000.0000.0000.0280.0240.0160.0130.0160.0130.0000.0000.017
HourCounters Average TurbineOk Avg. [h]0.0680.0000.0150.0000.0270.0000.0000.0230.0000.0570.0310.0810.0770.0110.0200.0170.0030.0030.0000.0000.0020.0130.0190.0190.0000.0220.0080.0030.0000.0000.0000.0000.0570.0200.0530.0890.0000.0050.0110.0360.0450.0340.0470.0000.0330.0110.0000.0000.0480.0210.0240.1020.0690.0320.0460.0680.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.4800.2890.0780.0000.4100.1960.5180.3711.0000.0000.0100.0000.0000.0000.0000.0920.0550.0000.0830.0620.0000.0460.0470.0000.0550.0170.0460.0710.0110.0000.000
HourCounters Average WindOk Avg. [h]0.0230.0000.0130.0130.0180.0440.0370.0530.0250.1000.1720.1160.1020.0000.0070.0000.0070.0000.0160.0110.0050.0300.0210.0580.0250.0340.0140.0060.0090.0000.0000.0000.0430.0320.1240.0540.0240.0100.0000.2200.1880.1740.1580.0000.1500.0800.1020.0790.1430.0710.0990.0800.1370.1510.0830.0820.0020.0000.0000.0070.0160.0300.0000.0010.0390.0000.0830.1250.0000.1360.0000.0490.0850.0000.0001.0000.0490.0100.0060.0000.0000.2250.0000.1400.1950.0540.1380.1460.0860.0000.0400.0190.1120.0260.0220.0000.005
HourCounters Average Yaw Avg. [h]0.0000.0000.0100.0140.0130.0160.0220.0120.0490.1130.0680.0550.1290.0000.0250.0000.0110.0120.0110.0210.0080.0360.0160.0220.0260.0390.0090.0080.0000.0250.0310.0230.0630.0680.0500.1330.0210.0000.0000.1230.1250.1360.1350.0060.1200.1150.1360.1530.1450.1020.1710.1350.1250.1200.2490.1620.0000.0000.0000.0090.0050.0140.0080.0000.0070.0030.0120.0110.0030.1120.0100.0000.0120.0070.0100.0491.0000.0000.0000.0000.0000.1250.0190.1310.1430.0140.1170.1420.0970.0000.0650.0590.0390.1190.0060.0110.000
Hydraulic Oil Temp. Avg. [°C]0.0000.0000.0330.0070.0010.0060.0000.0040.0130.0140.0050.0030.0000.0010.0000.0130.0000.0060.0300.0180.0200.0000.0110.0000.0000.0090.0190.0170.0250.0000.0000.0000.0000.0190.0000.0000.0180.0210.0120.0130.0000.0000.0000.0000.0150.0210.0000.0110.0060.0230.0000.0000.0140.0050.0050.0240.0000.0000.0000.0050.0180.0120.0000.0000.0120.0010.0240.0120.0000.0140.0020.0000.0250.0000.0000.0100.0001.0000.0290.0000.0000.0110.0270.0180.0050.0110.0080.0100.0000.0150.0060.0120.0000.0300.0000.0000.000
Nacelle Temp. Avg. [°C]0.0000.0000.0320.0000.0210.0050.0050.0000.0000.0110.0160.0000.0000.0130.0120.0950.0120.0690.0140.0060.0060.0040.0000.0000.0000.0200.0040.0490.0150.0030.0000.0070.0120.0000.0080.0080.0460.0560.0000.0100.0070.0050.0110.0060.0050.0130.0000.0020.0200.0200.0070.0160.0140.0000.0000.0000.0050.0000.0000.0000.0000.0070.0210.0000.0210.0120.0000.0000.0110.0000.0000.0000.0000.0000.0000.0060.0000.0291.0000.0000.0000.0120.0000.0160.0180.0080.0060.0260.0210.0000.0040.0000.0100.0000.0270.0000.004
Power factor set point0.2370.7500.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0960.0000.0000.0000.0000.3060.0000.0600.0000.0000.0000.0000.0001.0000.7500.0000.0000.0000.0020.0000.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.027
Power factor set point source0.2370.7500.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0960.0000.0000.0000.0000.3060.0000.0600.0000.0000.0000.0000.0000.7501.0000.0000.0000.0000.0020.0000.0000.0000.0000.0360.0000.0000.0000.0000.0000.0000.027
Production LatestAverage Active Power Gen 0 Avg. [W]0.0040.0000.0160.0280.0920.0310.0400.0530.0170.3870.2640.4280.3550.0050.0490.0000.0370.0190.0100.0580.0820.0600.0800.1390.0600.0560.0000.0090.0250.0170.0090.0250.3090.2100.3850.2740.0480.0000.0200.6090.2570.2530.2900.0070.2290.2230.2080.2530.3500.2460.2120.2720.6270.4290.3450.4050.0000.0130.0000.0360.0370.0480.0050.0090.0200.0020.1710.1180.0200.6300.0480.0000.1650.0500.0920.2250.1250.0110.0120.0000.0001.0000.0050.2220.7830.0430.4210.3920.4900.0300.3210.1880.3050.2380.0720.0000.055
Production LatestAverage Active Power Gen 1 Avg. [W]0.0000.0000.0220.0000.0060.1100.0540.0340.0080.0770.0300.1870.1430.0000.0050.0000.0610.0030.0000.0440.0410.0380.0530.0930.0190.0350.0140.0150.0000.0120.0210.0090.0550.0000.1580.0120.0190.0180.0330.0200.1640.1680.1710.0000.2110.0910.0930.0930.2310.0610.0830.1210.1630.1770.1850.2010.0000.0000.0020.0100.0080.0000.0000.0550.0340.0520.1360.0900.6150.2900.0000.0000.1410.0000.0550.0000.0190.0270.0000.0000.0000.0051.0000.0070.0000.2510.0870.2890.1760.0050.0480.0020.1370.0210.0160.0000.009
Production LatestAverage Active Power Gen 2 Avg. [W]0.0000.0000.0000.0050.0050.1030.0590.0770.0170.2850.1390.2910.2920.0000.0480.0000.0080.0190.0070.0170.0000.0620.0210.0340.0330.0240.0160.0230.0000.0000.0110.0150.1270.1830.1720.1770.0390.0180.0050.2370.3550.3780.4050.0030.4480.3200.3220.3570.4610.3310.3100.3420.3060.2820.1500.2320.0110.0240.0130.0000.0050.0300.0180.0100.0160.0000.0000.0000.3320.4970.0040.0000.0000.0000.0000.1400.1310.0180.0160.0000.0000.2220.0071.0000.1880.0760.2990.4820.2220.0070.1390.1530.1470.1400.0260.0000.007
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0160.0020.0130.0290.1100.0250.0360.0460.0280.3630.2640.4000.3350.0100.0440.0000.0390.0200.0240.0550.0890.0590.0750.1280.0590.0630.0000.0030.0260.0240.0200.0240.2990.2220.3510.2600.0630.0050.0220.5730.2390.2620.2590.0090.1940.2070.1910.2370.2700.2280.1870.2410.7020.4240.3670.4090.0050.0200.0060.0340.0350.0510.0170.0050.0130.0000.1510.1060.0000.5680.0520.0180.1420.0520.0830.1950.1430.0050.0180.0020.0020.7830.0000.1881.0000.0520.4020.2680.5920.0480.3130.1950.2770.2280.0740.0000.069
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0000.0000.0220.0200.0000.0080.0230.0000.0940.0550.2080.1800.0080.0100.0210.0540.0000.0030.0000.0240.0000.0000.0230.0070.0270.0000.0000.0000.0330.0340.0300.0000.0340.0240.0000.0000.0240.0170.0630.0070.0090.0010.0010.0170.0000.0000.0390.0000.0180.0250.0720.2060.1890.1220.1890.0070.0160.0080.0160.0150.0250.0000.0120.0000.0110.0710.0570.3200.1230.0000.0000.0740.0000.0620.0540.0140.0110.0080.0000.0000.0430.2510.0760.0521.0000.0760.0000.6280.0150.0000.0150.0130.0000.0060.0000.019
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0000.0000.0140.0160.0270.0100.0140.0570.0210.2720.0890.4470.5110.0050.0300.0000.0050.0310.0000.0000.0270.0050.0000.0490.0190.0240.0040.0170.0070.0210.0220.0150.1310.1310.2600.2970.0510.0210.0210.3780.0770.0850.0950.0000.1410.1480.2630.1810.1410.1340.2130.1800.5440.4090.3050.5060.0000.0000.0000.0000.0000.0100.0070.0190.0350.0110.0020.0000.1910.5120.0000.0000.0000.0000.0000.1380.1170.0080.0060.0000.0000.4210.0870.2990.4020.0761.0000.1460.4380.0970.1380.1190.1930.2450.0280.0000.138
Production LatestAverage Total Active Power Avg. [W]0.0000.0000.0200.0000.0180.2210.1230.0820.0300.2400.1520.1930.1980.0000.0370.0000.0120.0240.0150.0930.0710.1000.0850.0620.0730.0600.0000.0030.0090.0560.0650.0660.2030.1470.1670.1840.0410.0000.0620.2810.6280.6310.6790.0000.6330.3830.3610.3880.8570.4260.4240.4420.2220.1770.1380.1710.0100.0100.0050.0460.0390.0570.0090.0150.0180.0000.1110.0770.0540.2360.0000.0070.1130.0000.0460.1460.1420.0100.0260.0000.0000.3920.2890.4820.2680.0000.1461.0000.1740.0000.1990.1230.1420.1680.0530.0000.000
Production LatestAverage Total Reactive Power Avg. [var]0.0000.0000.0100.0000.0530.0240.0330.0630.0220.3420.1410.4880.3970.0110.0220.0150.0230.0170.0090.0300.0370.0380.0480.1100.0310.0550.0000.0040.0250.0100.0080.0010.1960.1360.2680.1580.0400.0210.0000.3490.1440.1630.1630.0000.1290.1380.1330.1900.1760.1420.1110.1960.7260.4970.3840.4720.0140.0270.0180.0040.0150.0160.0000.0180.0160.0160.0860.0550.2710.5310.0270.0060.0800.0280.0470.0860.0970.0000.0210.0000.0000.4900.1760.2220.5920.6280.4380.1741.0000.0140.1970.1320.2090.1330.0420.0000.038
Reactive power generator 0,Total accumulated [var]0.0330.0360.0000.0000.0000.0000.0000.0000.0000.0200.0180.0210.0650.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0130.0000.0350.0430.0000.0000.0080.0350.0000.0000.0000.0000.0000.0020.0110.0000.0000.0060.0090.0000.0210.0070.0100.0430.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0090.0000.0070.0210.0000.0440.0000.0240.0000.0000.0000.0150.0000.0360.0360.0300.0050.0070.0480.0150.0970.0000.0141.0000.0150.0000.0270.0360.0100.0000.266
Rotor RPM Avg. [RPM]0.0000.0000.0050.0290.0820.1230.0670.0790.0170.2860.1330.2410.2000.0000.0390.0130.0200.0110.0050.1270.1800.1460.1580.2030.1500.0670.0190.0150.0180.0130.0360.0460.7640.3260.3910.4210.0390.0090.0000.2170.1720.1760.1820.0050.1870.2090.1670.1880.1830.1890.1140.1680.2450.1830.2120.1710.0110.0130.0100.0360.0370.0390.0000.0010.0120.0000.1220.0910.0410.2720.0140.0000.1270.0160.0550.0400.0650.0060.0040.0000.0000.3210.0480.1390.3130.0000.1380.1990.1970.0151.0000.2960.3600.3970.0550.0000.040
Rotor RPM Max. [RPM]0.0030.0000.0070.0380.0880.0600.0660.0490.0210.2150.2520.1290.1450.0070.0330.0000.0190.0210.0100.0620.0780.0750.0890.0980.1100.1250.0110.0000.0130.0000.0000.0130.3500.7780.1270.2570.0440.0200.0000.1290.1050.1090.1140.0000.1340.1840.1420.1780.1110.1630.0910.1390.1700.1560.0840.0940.0100.0000.0000.0280.0190.0180.0070.0000.0130.0100.0590.0640.0510.1970.0100.0000.0640.0130.0170.0190.0590.0120.0000.0000.0000.1880.0020.1530.1950.0150.1190.1230.1320.0000.2961.0000.1060.2090.0530.0000.000
Rotor RPM Min. [RPM]0.0050.0000.0000.0040.0530.0810.0390.1180.0140.2190.0790.3200.2120.0000.0130.0070.0000.0030.0070.0920.1040.0900.1170.1830.0680.0130.0220.0240.0100.0180.0130.0280.3370.1160.7840.2070.0430.0150.0070.2150.1080.1050.1210.0000.1240.0820.1360.0790.1270.0680.1330.0730.2610.2370.2760.1950.0000.0010.0000.0300.0330.0410.0050.0200.0270.0030.0670.0400.1630.3470.0150.0000.0710.0160.0460.1120.0390.0000.0100.0000.0000.3050.1370.1470.2770.0130.1930.1420.2090.0270.3600.1061.0000.1810.0440.0000.034
Rotor RPM StdDev [RPM]0.0000.0000.0070.0250.0310.0490.0460.0410.0510.2170.0790.2030.3500.0000.0310.0000.0380.0360.0100.0850.1070.0840.0870.0910.0980.0800.0000.0140.0100.0110.0190.0310.4020.2440.2060.7300.0420.0050.0160.2010.1210.1350.1330.0000.1600.2020.2290.2280.1550.1820.1810.2220.1850.1420.1530.2840.0000.0020.0000.0350.0220.0390.0050.0000.0100.0000.0830.0590.0050.2000.0160.0000.0850.0130.0710.0260.1190.0300.0000.0000.0000.2380.0210.1400.2280.0000.2450.1680.1330.0360.3970.2090.1811.0000.0350.0000.046
Spinner Temp. Avg. [°C]0.0000.0000.0210.0240.0340.0160.0140.0220.0100.0510.0380.0550.0310.0000.0510.0090.0040.0140.0000.0060.0220.0160.0160.0370.0110.0210.0050.0070.0020.0000.0000.0000.0530.0690.0470.0370.0100.0000.0030.0630.0470.0480.0490.0000.0440.0310.0360.0330.0470.0370.0410.0510.0570.0280.0360.0330.0090.0000.0020.0000.0100.0000.0090.0000.0000.0110.0320.0290.0140.0530.0000.0000.0320.0000.0110.0220.0060.0000.0270.0000.0000.0720.0160.0260.0740.0060.0280.0530.0420.0100.0550.0530.0440.0351.0000.0000.002
Total Active power [W]0.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.000
Total reactive power [var]0.0240.0270.0000.0050.0180.0000.0000.0000.0000.0330.0070.0340.0790.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0070.0000.0040.0100.0000.0000.0130.0120.0410.0000.0400.0560.0000.0000.0120.0480.0090.0090.0080.0000.0070.0060.0120.0050.0000.0070.0120.0000.0580.0250.0220.0710.0000.0000.0000.0020.0050.0000.0000.0000.0000.0000.0120.0000.0080.0440.0000.0330.0000.0170.0000.0050.0000.0000.0040.0270.0270.0550.0090.0070.0690.0190.1380.0000.0380.2660.0400.0000.0340.0460.0020.0001.000

Missing values

2025-05-14T19:18:25.184994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-14T19:18:25.908634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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72020-01-01 01:10:0000000100001000000100000000000000000001000000000000000110000000000000000000000000000000000000000000000000000000000000000000000000
82020-01-01 01:20:0000000000001000000000000010000000000001000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
92020-01-01 01:30:0000000011000000000001010011000000000001000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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